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Geometric Morphometrics In Anthropology
The study of geometric morphometrics in anthropology has made a major impact on the field of morphometrics by aiding in some of the technological and methodological advancements. Geometric morphometrics is an approach that studies shape using Cartesian landmark and semilandmark coordinates that are capable of capturing morphologically distinct shape variables. The landmarks can be analyzed using various statistical techniques separate from size, position, and orientation so that the only variables being observed are based on morphology. Geometric morphometrics is used to observe variation in numerous formats, especially those pertaining to evolutionary and biological processes, which can be used to help explore the answers to a lot of questions in physical anthropology. Geometric morphometrics is part of a larger subfield in anthropology, which has more recently been named virtual anthropology. Virtual anthropology looks at virtual morphology, the use of virtual copies of specimens ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Morphometric Landmarks On A Eurasian Perch (Perca Fluviatilis) - Journal
Morphometrics (from Greek μορϕή ''morphe'', "shape, form", and -μετρία ''metria'', "measurement") or morphometry refers to the quantitative analysis of ''form'', a concept that encompasses size and shape. Morphometric analyses are commonly performed on organisms, and are useful in analyzing their fossil record, the impact of mutations on shape, developmental changes in form, covariances between ecological factors and shape, as well for estimating quantitative-genetic parameters of shape. Morphometrics can be used to quantify a trait of evolutionary significance, and by detecting changes in the shape, deduce something of their ontogeny, function or evolutionary relationships. A major objective of morphometrics is to statistically test hypotheses about the factors that affect shape. "Morphometrics", in the broader sense, is also used to precisely locate certain areas of organs such as the brain, and in describing the shapes of other things. Forms Three general appro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Analysis
Statistical inference is the process of using data analysis to infer properties of an underlying distribution of probability.Upton, G., Cook, I. (2008) ''Oxford Dictionary of Statistics'', OUP. . Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population. In machine learning, the term ''inference'' is sometimes used instead to mean "make a prediction, by evaluating an already trained model"; in this context inferring properties of the model is referred to as ''training'' or ''learning'' (rather than ''inference''), and using a model for prediction is referred to as ''inference'' (instead of ''prediction''); ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Endocasts
An endocast is the internal cast of a hollow object, often referring to the cranial vault in the study of brain development in humans and other organisms. Endocasts can be artificially made for examining the properties of a hollow, inaccessible space, or they may occur naturally through fossilization. Cranial endocasts Artificial casts Endocasts of the inside of the neurocranium (braincase) are often made in paleoanthropology to study brain structures and hemispheric specialization in extinct human ancestors. While an endocast can not directly reveal brain structure, it can allow scientists to gauge the size of areas of the brain situated close to the surface, notably Wernicke's and Broca's areas, responsible for interpreting and producing speech. Traditionally, the casting material is some form of rubber or rubber-like material. The openings to the brain cavity, except for the ''foramen magnum'', are closed, and the liquid rubber is slushed around in the empty cranial vault a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gyrification
Gyrification is the process of forming the characteristic folds of the cerebral cortex. The peak of such a fold is called a ''gyrus'' (pl. ''gyri''), and its trough is called a '' sulcus'' (pl. ''sulci''). The neurons of the cerebral cortex reside in a thin layer of gray matter, only 2–4 mm thick, at the surface of the brain. Much of the interior volume is occupied by white matter, which consists of long axonal projections to and from the cortical neurons residing near the surface. Gyrification allows a larger cortical surface area and hence greater cognitive functionality to fit inside a smaller cranium. In most mammals, gyrification begins during fetal development. Primates, cetaceans, and ungulates have extensive cortical gyri, with a few species exceptions, while rodents generally have none. Gyrification in some animals, for example the ferret, continues well into postnatal life. Gyrification during human brain development As fetal development proceeds, gyri ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parietal Cortex
The parietal lobe is one of the four major lobes of the cerebral cortex in the brain of mammals. The parietal lobe is positioned above the temporal lobe and behind the frontal lobe and central sulcus. The parietal lobe integrates sensory information among various modalities, including spatial sense and navigation (proprioception), the main sensory receptive area for the sense of touch in the somatosensory cortex which is just posterior to the central sulcus in the postcentral gyrus, and the dorsal stream of the visual system. The major sensory inputs from the skin (touch, temperature, and pain receptors), relay through the thalamus to the parietal lobe. Several areas of the parietal lobe are important in language processing. The somatosensory cortex can be illustrated as a distorted figure – the cortical homunculus (Latin: "little man") in which the body parts are rendered according to how much of the somatosensory cortex is devoted to them. The superior parietal lobule and in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Temporal Lobe
The temporal lobe is one of the four Lobes of the brain, major lobes of the cerebral cortex in the brain of mammals. The temporal lobe is located beneath the lateral fissure on both cerebral hemispheres of the mammalian brain. The temporal lobe is involved in processing sensory input into derived meanings for the appropriate retention of visual memory, language comprehension, and emotion association. ''Temporal'' refers to the head's Temple (anatomy), temples. Structure The Temple (anatomy)#Etymology, temporal Lobe (anatomy), lobe consists of structures that are vital for declarative or long-term memory. Declarative memory, Declarative (denotative) or Explicit memory, explicit memory is conscious memory divided into semantic memory (facts) and episodic memory (events). Medial temporal lobe structures that are critical for long-term memory include the hippocampus, along with the surrounding Hippocampal formation, hippocampal region consisting of the Perirhinal cortex, perirhinal, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Visual Cortex
The visual cortex of the brain is the area of the cerebral cortex that processes visual information. It is located in the occipital lobe. Sensory input originating from the eyes travels through the lateral geniculate nucleus in the thalamus and then reaches the visual cortex. The area of the visual cortex that receives the sensory input from the lateral geniculate nucleus is the primary visual cortex, also known as visual area 1 ( V1), Brodmann area 17, or the striate cortex. The extrastriate areas consist of visual areas 2, 3, 4, and 5 (also known as V2, V3, V4, and V5, or Brodmann area 18 and all Brodmann area 19). Both hemispheres of the brain include a visual cortex; the visual cortex in the left hemisphere receives signals from the right visual field, and the visual cortex in the right hemisphere receives signals from the left visual field. Introduction The primary visual cortex (V1) is located in and around the calcarine fissure in the occipital lobe. Each hemisphere's V1 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Allometric
Allometry is the study of the relationship of body size to shape, anatomy, physiology and finally behaviour, first outlined by Otto Snell in 1892, by D'Arcy Thompson in 1917 in ''On Growth and Form'' and by Julian Huxley in 1932. Overview Allometry is a well-known study, particularly in statistical shape analysis for its theoretical developments, as well as in biology for practical applications to the differential growth rates of the parts of a living organism's body. One application is in the study of various insect species (e.g., Hercules beetles), where a small change in overall body size can lead to an enormous and disproportionate increase in the dimensions of appendages such as legs, antennae, or horns The relationship between the two measured quantities is often expressed as a power law equation (Allometric equation) which expresses a remarkable scale symmetry: : y = kx^a \,\! or in a logarithmic form: : \log y = a \log x + \log k\,\! or similarly \ln y = a \ln x ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multivariate Statistics
Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to each other. The practical application of multivariate statistics to a particular problem may involve several types of univariate and multivariate analyses in order to understand the relationships between variables and their relevance to the problem being studied. In addition, multivariate statistics is concerned with multivariate probability distributions, in terms of both :*how these can be used to represent the distributions of observed data; :*how they can be used as part of statistical inference, particularly where several different quantities are of interest to the same analysis. Certain types of problems involving multivariate data, for example simple linear regression an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Partial Least Squares Regression
Partial least squares regression (PLS regression) is a statistical method that bears some relation to principal components regression; instead of finding hyperplanes of maximum variance between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new space. Because both the ''X'' and ''Y'' data are projected to new spaces, the PLS family of methods are known as bilinear factor models. Partial least squares discriminant analysis (PLS-DA) is a variant used when the Y is categorical. PLS is used to find the fundamental relations between two matrices (''X'' and ''Y''), i.e. a latent variable approach to modeling the covariance structures in these two spaces. A PLS model will try to find the multidimensional direction in the ''X'' space that explains the maximum multidimensional variance direction in the ''Y'' space. PLS regression is particularly suited when the matrix of predictors has more ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Principal Components Analysis
Principal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data. Many studies use the first two principal components in order to plot the data in two dimensions and to visually identify clusters of closely related data points. Principal component analysis has applications in many fields such as population genetics, microbiome studies, and atmospheric science. The principal components of a collection of points in a real coordinate space are a sequence of p unit vectors, where the i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Generalized Procrustes Analysis
Generalized Procrustes analysis (GPA) is a method of statistical analysis that can be used to compare the shapes of objects, or the results of surveys, interviews, or panels. It was developed for analysing the results of free-choice profiling, a survey technique which allows respondents (such as sensory panelists) to describe a range of products in their own words or language. GPA is one way to make sense of free-choice profiling data; other ways can be multiple factor analysis (MFA), or the STATIS method. The method was first published by J. C. Gower in 1975. Generalized Procrustes analysis estimates the scaling factor applied to respondent scale usage, generating a weighting factor that is used to compensate for individual scale usage differences. Unlike measures such as a principal component analysis, GPA uses individual level data and a measure of variance is utilized in the analysis. The Procrustes distance provides a metric to minimize in order to superimpose a pair of s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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